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            <td width="35%" class="headerValue"><a href="../../../index.html">top level</a> - <a href="index.html">src/caffe/layers</a> - euclidean_loss_layer.cpp<span style="font-size: 80%;"> (source / <a href="euclidean_loss_layer.cpp.func-sort-c.html">functions</a>)</span></td>
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            <td class="headerItem">Test:</td>
            <td class="headerValue">code analysis</td>
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            <td class="headerItem">Lines:</td>
            <td class="headerCovTableEntry">2</td>
            <td class="headerCovTableEntry">22</td>
            <td class="headerCovTableEntryLo">9.1 %</td>
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            <td class="headerItem">Date:</td>
            <td class="headerValue">2020-09-11 22:50:33</td>
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            <td class="headerItem">Functions:</td>
            <td class="headerCovTableEntry">2</td>
            <td class="headerCovTableEntry">14</td>
            <td class="headerCovTableEntryLo">14.3 %</td>
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            <td class="headerValueLeg">            Lines:
            <span class="coverLegendCov">hit</span>
            <span class="coverLegendNoCov">not hit</span>
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<pre class="sourceHeading">          Line data    Source code</pre>
<pre class="source">
<a name="1"><span class="lineNum">       1 </span>            : #include &lt;vector&gt;</a>
<span class="lineNum">       2 </span>            : 
<span class="lineNum">       3 </span>            : #include &quot;caffe/layers/euclidean_loss_layer.hpp&quot;
<span class="lineNum">       4 </span>            : #include &quot;caffe/util/math_functions.hpp&quot;
<span class="lineNum">       5 </span>            : 
<span class="lineNum">       6 </span>            : namespace caffe {
<a name="7"><span class="lineNum">       7 </span>            : </a>
<span class="lineNum">       8 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">       9 </span><span class="lineNoCov">          0 : void EuclideanLossLayer&lt;Dtype&gt;::Reshape(</span>
<span class="lineNum">      10 </span>            :   const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom, const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top) {
<span class="lineNum">      11 </span><span class="lineNoCov">          0 :   LossLayer&lt;Dtype&gt;::Reshape(bottom, top);</span>
<span class="lineNum">      12 </span><span class="lineNoCov">          0 :   CHECK_EQ(bottom[0]-&gt;count(1), bottom[1]-&gt;count(1))</span>
<span class="lineNum">      13 </span>            :       &lt;&lt; &quot;Inputs must have the same dimension.&quot;;
<span class="lineNum">      14 </span><span class="lineNoCov">          0 :   diff_.ReshapeLike(*bottom[0]);</span>
<span class="lineNum">      15 </span><span class="lineNoCov">          0 : }</span>
<a name="16"><span class="lineNum">      16 </span>            : </a>
<span class="lineNum">      17 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">      18 </span><span class="lineNoCov">          0 : void EuclideanLossLayer&lt;Dtype&gt;::Forward_cpu(const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom,</span>
<span class="lineNum">      19 </span>            :     const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top) {
<span class="lineNum">      20 </span><span class="lineNoCov">          0 :   int count = bottom[0]-&gt;count();</span>
<span class="lineNum">      21 </span><span class="lineNoCov">          0 :   caffe_sub(</span>
<span class="lineNum">      22 </span>            :       count,
<span class="lineNum">      23 </span>            :       bottom[0]-&gt;cpu_data(),
<span class="lineNum">      24 </span>            :       bottom[1]-&gt;cpu_data(),
<span class="lineNum">      25 </span>            :       diff_.mutable_cpu_data());
<span class="lineNum">      26 </span><span class="lineNoCov">          0 :   Dtype dot = caffe_cpu_dot(count, diff_.cpu_data(), diff_.cpu_data());</span>
<span class="lineNum">      27 </span><span class="lineNoCov">          0 :   Dtype loss = dot / bottom[0]-&gt;num() / Dtype(2);</span>
<span class="lineNum">      28 </span><span class="lineNoCov">          0 :   top[0]-&gt;mutable_cpu_data()[0] = loss;</span>
<span class="lineNum">      29 </span><span class="lineNoCov">          0 : }</span>
<a name="30"><span class="lineNum">      30 </span>            : </a>
<span class="lineNum">      31 </span>            : template &lt;typename Dtype&gt;
<span class="lineNum">      32 </span><span class="lineNoCov">          0 : void EuclideanLossLayer&lt;Dtype&gt;::Backward_cpu(const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; top,</span>
<span class="lineNum">      33 </span>            :     const vector&lt;bool&gt;&amp; propagate_down, const vector&lt;Blob&lt;Dtype&gt;*&gt;&amp; bottom) {
<span class="lineNum">      34 </span><span class="lineNoCov">          0 :   for (int i = 0; i &lt; 2; ++i) {</span>
<span class="lineNum">      35 </span><span class="lineNoCov">          0 :     if (propagate_down[i]) {</span>
<span class="lineNum">      36 </span><span class="lineNoCov">          0 :       const Dtype sign = (i == 0) ? 1 : -1;</span>
<span class="lineNum">      37 </span><span class="lineNoCov">          0 :       const Dtype alpha = sign * top[0]-&gt;cpu_diff()[0] / bottom[i]-&gt;num();</span>
<span class="lineNum">      38 </span><span class="lineNoCov">          0 :       caffe_cpu_axpby(</span>
<span class="lineNum">      39 </span>            :           bottom[i]-&gt;count(),              // count
<span class="lineNum">      40 </span>            :           alpha,                              // alpha
<span class="lineNum">      41 </span>            :           diff_.cpu_data(),                   // a
<span class="lineNum">      42 </span>            :           Dtype(0),                           // beta
<span class="lineNum">      43 </span>            :           bottom[i]-&gt;mutable_cpu_diff());  // b
<span class="lineNum">      44 </span>            :     }
<span class="lineNum">      45 </span>            :   }
<span class="lineNum">      46 </span><span class="lineNoCov">          0 : }</span>
<a name="47"><span class="lineNum">      47 </span>            : </a>
<span class="lineNum">      48 </span>            : #ifdef CPU_ONLY
<span class="lineNum">      49 </span><span class="lineNoCov">          0 : STUB_GPU(EuclideanLossLayer);</span>
<span class="lineNum">      50 </span>            : #endif
<a name="51"><span class="lineNum">      51 </span>            : </a>
<span class="lineNum">      52 </span>            : INSTANTIATE_CLASS(EuclideanLossLayer);
<a name="53"><span class="lineNum">      53 </span><span class="lineCov">          3 : REGISTER_LAYER_CLASS(EuclideanLoss);</span></a>
<span class="lineNum">      54 </span>            : 
<span class="lineNum">      55 </span><span class="lineCov">          3 : }  // namespace caffe</span>
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